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Investigating the Impacts of Processing Uncertainty and Variability on Residual Stresses and Deformations in Aerospace Composites Manufacturing
Investigating the Impacts of Processing Uncertainty and Variability on Residual Stresses and Deformations in Aerospace Composites Manufacturing
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211151312
- ISBN
- 9798383226339
- DDC
- 620
- 서명/저자
- Investigating the Impacts of Processing Uncertainty and Variability on Residual Stresses and Deformations in Aerospace Composites Manufacturing
- 발행사항
- [Sl] : University of Washington, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 185 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-01, Section: B.
- 주기사항
- Advisor: Zobeiry, Navid.
- 학위논문주기
- Thesis (Ph.D.)--University of Washington, 2024.
- 초록/해제
- 요약Despite significant advancements in materials formulation and manufacturing technologies, high levels of uncertainty persist in the raw material and production of composite-intensive aircraft. One such uncertainty source is the impact of material and processing variabilities on residual stresses and deformations in composite parts, which negatively affects the assembly process of aerostructures. This research investigates these phenomena, focusing on Toray T800S/3900-2B, an aerospace-grade material used in the production of several aircraft such as the Boeing 787. The initial research phase involves a comprehensive characterization of various material properties, manufacturing phenomena, and processing variables that may significantly impact process-induced deformations (PIDs) but are surrounded by high uncertainty. Investigations include assessing the impact of release coating on tool surface properties, examining the influence of processing conditions on T800S/3900-2B, and evaluating the role of processing variabilities in tool-part interactions. Next, a novel machine learning (ML) method is developed for accelerated composites characterization, which demonstrates substantial time and cost savings compared to traditional methods. A parametric exploration into the effects of layup and cure cycle procedures on PIDs is conducted, and potential mitigation strategies are proposed. Next, an innovative methodology for efficiently predicting PIDs and analyzing composites using multi-fidelity simulation and theory-guided machine learning (TGML) is devised. Lastly, a novel process optimization approach for minimizing PIDs in composite parts without the use of any material characterization or process simulation is introduced. This research aims to provide a comprehensive framework for further exploration and potential mitigation of PIDs in aerospace composites manufacturing.
- 일반주제명
- Engineering
- 일반주제명
- Materials science
- 일반주제명
- Industrial engineering
- 일반주제명
- Aerospace engineering
- 키워드
- Aerostructures
- 기타저자
- University of Washington Materials Science and Engineering
- 기본자료저록
- Dissertations Abstracts International. 86-01B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■006m o d
■007cr#unu||||||||
■020 ▼a9798383226339
■035 ▼a(MiAaPQ)AAI31237309
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a620
■1001 ▼aSchoenholz, Caleb.
■24510▼aInvestigating the Impacts of Processing Uncertainty and Variability on Residual Stresses and Deformations in Aerospace Composites Manufacturing
■260 ▼a[Sl]▼bUniversity of Washington▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a185 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-01, Section: B.
■500 ▼aAdvisor: Zobeiry, Navid.
■5021 ▼aThesis (Ph.D.)--University of Washington, 2024.
■520 ▼aDespite significant advancements in materials formulation and manufacturing technologies, high levels of uncertainty persist in the raw material and production of composite-intensive aircraft. One such uncertainty source is the impact of material and processing variabilities on residual stresses and deformations in composite parts, which negatively affects the assembly process of aerostructures. This research investigates these phenomena, focusing on Toray T800S/3900-2B, an aerospace-grade material used in the production of several aircraft such as the Boeing 787. The initial research phase involves a comprehensive characterization of various material properties, manufacturing phenomena, and processing variables that may significantly impact process-induced deformations (PIDs) but are surrounded by high uncertainty. Investigations include assessing the impact of release coating on tool surface properties, examining the influence of processing conditions on T800S/3900-2B, and evaluating the role of processing variabilities in tool-part interactions. Next, a novel machine learning (ML) method is developed for accelerated composites characterization, which demonstrates substantial time and cost savings compared to traditional methods. A parametric exploration into the effects of layup and cure cycle procedures on PIDs is conducted, and potential mitigation strategies are proposed. Next, an innovative methodology for efficiently predicting PIDs and analyzing composites using multi-fidelity simulation and theory-guided machine learning (TGML) is devised. Lastly, a novel process optimization approach for minimizing PIDs in composite parts without the use of any material characterization or process simulation is introduced. This research aims to provide a comprehensive framework for further exploration and potential mitigation of PIDs in aerospace composites manufacturing.
■590 ▼aSchool code: 0250.
■650 4▼aEngineering
■650 4▼aMaterials science
■650 4▼aIndustrial engineering
■650 4▼aAerospace engineering
■653 ▼aAerospace composites manufacturing
■653 ▼aProbabilistic machine learning
■653 ▼aProcess-induced deformations
■653 ▼aResidual stresses
■653 ▼aAerostructures
■690 ▼a0794
■690 ▼a0537
■690 ▼a0800
■690 ▼a0546
■690 ▼a0538
■71020▼aUniversity of Washington▼bMaterials Science and Engineering.
■7730 ▼tDissertations Abstracts International▼g86-01B.
■790 ▼a0250
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17161117▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
